1. Field of the Invention
The present invention relates to a speech privacy processing method used when an analog speech signal is transmitted on an analog line whose transmission path band is limited and, more particularly, to a speech privacy processing method by an FFT scrambler method utilizing fast Fourier transformation and an apparatus therefore.
2. Related Background Art
Along with a recent increase in communication traffic, secret communication techniques for preventing a communication content from being known to a third party have gained their importances. Of these techniques, a privacy processing technique is a technique for performing secret communication on a transmission path whose band is limited, e.g., a general public line. Originally, in privacy processing of a speech signal, when a speech signal is subjected to complicated privacy processing to enhance a degree of privacy, quality of a descrambled speech signal is degraded. On the contrary, when degradation of the quality is to be avoided, a sufficient privacy strength cannot be obtained. As a method of simultaneously attaining secrecy and protection of an analog speech signal and high quality of a descrambled speech signal, a coefficient substitution method (FFT scrambler method) using fast Fourier transformation (to be referred to as FFT hereinafter) is known.
The prior art will be described below with reference to the accompanying drawings.
FIGS. 2A and 2B are block diagrams of a privacy processing apparatus of an analog speech signal by a conventional FFT scrambler method. In FIG. 2A, an analog speech signal x(t}to be subjected to privacy processing is input from an input terminal 31 to an A/D converter 32 and is converted to discrete signals x(n) (n=0, 1, 2, . . . ). The sample values are framed in units of N points (=one frame) by a framing circuit 33 In this case, frame sync data 38a indicating the beginning of each frame is supplied to a sync signal generator 38, thereby generating a frame sync signal 38b.
FIG. 3A shows a time waveform of an original signal, and its frame. This frame is input to an N-point FFT processor 34 to obtain n FFT coefficients X(k) (k=0, 1, . . . , n-1) from N time waveform sample values x(n) (n=0, 1, . . . , n-1). A digital signal x(n) obtained as a result of sampling of an input speech signal is expressed by: EQU x(n)=.lambda.A(.lambda.) cos (.alpha..multidot..lambda.n)+.theta.(.lambda.))
A discrete Fourier coefficient X(k) obtained from the FFT processor 34 is given by: ##EQU1## (k=0, 1, . . . , n-1) FIG. 3B(a) shows N FFT coefficients X(k) (k=0, 1, . . . , N-1) of one frame.
The N FFT coefficients are subjected to random substitution by a scrambler 35. FIG. 3B(b) partially shows this state. When N sample values Y(0), Y(1),..., Y(N-1) on the frequency axis obtained in this manner are input to an IFFT (Inverse Fast Fourier Transformation) processor 36, N sample values y(n) (n=0, 1, . . . , N) of a privacy signal to be calculated can be obtained. These sample values are converted to an analog privacy signal y(t) by a D/A converter 37, and the converted signal is transmitted onto a transmission path. FIG. 3C shows the privacy signal y(t). In this case, ##EQU2## (n=0, 1, . . . , N-1)
As can be seen from FIG. 3B, the privacy signal y(t) can be transmitted in the same frequency band as that of the original speech signal. When the signal y(t) is sent onto a transmission path, the frame sync signals 38b generated by the sync signal generator 38 and indicating a boundary of each frame are added to the signal y(t).
At a receiver side, a sync signal extractor 39 extracts the frame sync signals added at a transmitter side from the input privacy signal Thereafter, the privacy signal is converted into a digital signal by an A/D converter 40, and is divided into frames by a frame sync circuit 41 in accordance with the extracted frame sync signals. N sample values y(0), y(1) , . . . , y(N-1) of one frame are converted to sample values Y(k) (k=0, 1, . . . , N-1) in a frequency range by an FFT processor 42, and the converted sample values are then subjected to inverse transformation processing (descrambling) to the scrambling processing at the transmitter side by a descrambler 43, thus obtaining X(k) (k=0, 1, . . . , N-1). The output from the descrambler 35 is subjected to inverse discrete Fourier transformation by an N-point IFFT processor 44, and the transformed signal is then converted to an analog signal by a D/A converter 45. As a result, a descrambled original speech signal x(t) is output from an output terminal 46.
In the above method, as the number N of samples in one frame is larger, privacy processing performance is improved, and FFT coefficients obtained by the FFT processor are approximate to true frequency spectrum components. Therefore, quality of a descrambled speech signal is good. However, if the value N is increased, a processing delay time required in FFT and IFFT is increased. Therefore, the upper limit of the value N is determined according to an allowable maximum delay time.
Since FFT calculations can be most efficiently made by the butterfly algorithm when N is a power of 2, a maximum power of 2 which does not exceed the above-mentioned upper limit is adopted as the value N.
As described above, in a speech privacy processing apparatus using FFT, a privacy signal can be transmitted in the same band as an original signal, and quality of a descrambled speech signal is relatively good. However, since this apparatus adopts FFT, the following drawbacks are posed. More specifically, as a frequency becomes higher, the hearing resolution of a person is degraded accordingly. However, FFT analysis has the same resolution at any frequency. For this reason, even if FFT coefficients in a high frequency band are subjected to substitution processing such as a scrambler, such processing is redundant (wasteful) in terms of privacy processing. In some cases, a large number of invalid substitution patterns which cannot provide a sufficient privacy effect may be generated.
FIG. 4 shows this situation. FIG. 4 explains invalid substitution patterns generated by substitution processing by a scrambler with 10 samples/frame. 10 coefficients X(1), X(2) , . . . , X(10) obtained by FFT of an input original signal are rearranged by the scrambler on a frequency axis to be converted to Y(1), Y(2) , . . . , Y(10). In this case, FFT coefficients X(7), X(8), X(9), and X(10) are present in a high-frequency range in which the sense of hearing of a person is degraded. Upon substitution by the scrambler, Y(7), Y(8), Y(9), and Y(10) are obtained by randomly reordering X(7) to X(10). A frequency component of a privacy signal in a low-frequency range is Y(k)=X(k) (k=1, 2, . . . , 6), i.e., is the same as that of an original signal. When IFFT processing is executed after such substitution to obtain a privacy signal, random coefficient substitution in a high-frequency range does not contribute to a privacy strength due to degradation of hearing resolution. Therefore, if a wiretapper wiretaps the resultant privacy signal, he can easily infer an original speech signal.
As described above, in a conventional speech privacy processing apparatus using FFT, since FFT has the same resolution in a high-frequency range unlike the sense of hearing of a person, a large number of redundant (invalid) substitution patterns are generated, resulting in a degraded privacy effect.